# pip install -U transformers accelerate
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("sasha/dog-food-convnext-tiny-224")
model = AutoModelForImageClassification.from_pretrained("sasha/dog-food-convnext-tiny-224", device_map="auto")Quick Links
dog-food-convnext-tiny-224
This model was trained on the train split of the Dogs vs Food dataset -- try training your own using the
the demo on Google Colab!
Example Images
dog
food
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Dataset used to train sasha/dog-food-convnext-tiny-224
Evaluation results
- Accuracy on Dog Foodself-reported1.000
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sasha/dog-food-convnext-tiny-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")